Erschienen in:
Journal of Physics: Conference Series, 1933 (2021) 1, Seite 012050
Sprache:
Nicht zu entscheiden
DOI:
10.1088/1742-6596/1933/1/012050
ISSN:
1742-6588;
1742-6596
Entstehung:
Anmerkungen:
Beschreibung:
Abstract This study aims to predict Covid-19 data in Indonesia using LSTM machines learning and GRU using python. As a comparison, two datasets from other countries which have strong correlation were used. The dataset is of the ourworldindata.org page. The results of the LSTM model with epoch 15, RMSE 68,417 require rapid processing time and better accuracy than GRU with epoch 400, RMSE 90,173. The results from Covid-19 data processing in Indonesia have a robust correlation with Covid-19 data in Azerbaijan, Bangladesh, Bhutan, Cape Verde, Curacao, Slovenia, South Africa, and Thailand. The epoch characteristics of LSTM and GRU are a challenge since the amount of Covid-19 data is relatively minor.